Jan 2, 2024 · We propose RPEMHC, a new deep learning approach based on residue-residue pair encoding to predict the binding affinity between peptides and MHC.
Jan 4, 2024 · We propose RPEMHC, a new deep learning approach based on residue–residue pair encoding to predict the binding affinity between peptides and MHC.
Jan 4, 2024 · Results In this work, we propose RPEMHC, a new deep learning approach based on residue-residue pair encoding to predict the binding affinity ...
RPEMHC: improved prediction of MHC–peptide binding affinity by a deep learning approach based on residue–residue pair encoding. https://doi.org/10.1093 ...
Performance comparison between RPEMHC and RPEMHC-CA under five-fold cross-validation on IEDB2016.a. Method . Average . All . AUC . PCC . AUC . PCC . RPEMHC ...
RPEMHC: improved prediction of MHC-peptide binding affinity by a deep learning approach based on residue-residue pair encoding. Wang X, Wu T, Jiang Y, Chen ...
Apr 18, 2020 · ... , Qiang Lyu, . RPEMHC: improved prediction of MHC–peptide binding affinity by a deep learning approach based on residue–residue pair encoding.
People also ask
Which components of MHC I make up the peptide-binding cleft?
What is the binding of peptide to MHC?
RPEMHC: improved prediction of MHC–peptide binding affinity by a deep learning approach based on residue–residue pair encoding. Xuejiao Wang, Tingfang Wu ...
Jul 9, 2024 · RPEMHC (Wang et al., 2024) is a deep learning approach that aims to improve the prediction of MHC-peptide binding affinity by utilizing a ...
Apr 1, 2024 · We developed ConvNeXt-MHC, a method for predicting MHC-I-peptide binding affinity. It introduces a degenerate encoding approach to enhance well-established ...
Missing: RPEMHC: | Show results with:RPEMHC: